What to Do When AI Makes Things Up About Your Brand
AI models sometimes state false things about your brand with full confidence. Here is how to spot it and reduce the damage.
A hallucination, in the context of generative AI, is a statement the model presents as fact even though it is false. It is not a deliberate lie. The model predicts the most likely next word, and sometimes the most likely word does not match reality. When that happens with your brand, the result can be a price you never charged, a feature you do not offer or an integration that does not exist.
The trouble is that this text reaches the user in a confident, well written tone, so it looks true. If someone asks ChatGPT about your company and gets invented data, that person forms a wrong impression before ever visiting your site.
How to recognise a hallucination about your brand
The most direct way is to ask. Put specific questions to ChatGPT, Gemini and Perplexity about your product, your prices, your plans and your location. Repeat the questions with small variations, because the answer shifts depending on how you phrase it.
- Wrong numbers, such as prices, discounts or founding year.
- Features or products attributed to your brand that do not exist.
- Mix ups with a competitor that has a similar name.
- Claims about regions or languages you do not serve.
A common hallucination is blending your brand with another in the same sector. The model fills the gap with what it knows about the category.
Why it happens
Several causes combine. Understanding them helps you decide where to act.
Scarce or contradictory information
If your site says one price, a comparison site says another and an old press note says a third, the model has no clear source. When in doubt, it invents something plausible.
Stale data in the training set
Models learn from text up to a cutoff date. If you changed your price or name recently, they may keep repeating the old version.
Few reliable sources citing you
When almost nobody talks about you on authoritative sites, the model has little verifiable material and leans on guesses.
How to fix it
You cannot edit the model's mind, but you can improve what it learns and what it finds when it answers in real time.
Actions that reduce hallucinations
- Publish key data (price, plans, features) explicitly and as text, not only inside images.
- Keep a single version of each fact across your whole site. Consistency matters more than repetition.
- Use a facts page or an FAQ section with clear, direct answers.
- Earn mentions in sources the AI tends to consult, such as sector media and serious directories.
- Update dates and remove old prices that still float around the web.
The competitor mix up case
One very specific kind of hallucination deserves separate attention. The model confuses you with another company, usually because your names resemble each other or because you compete in the same niche. The result is that it attributes features, prices or reviews to your brand that actually belong to someone else. Sometimes it even blends both in equal parts, creating a hybrid company that does not exist.
To reduce this risk it helps to reinforce what makes you unique in your site's text. A clear full name, a specific product description and a mention of your market or language help the model tell you apart from the neighbour. If your name is generic or very common, publishing enough context so there is no doubt about who you are gains importance.
The blurrier your identity online, the easier it is for AI to fill the gaps with someone else's data.
What does not work
It is worth ruling out a few shortcuts. Repeating the correct fact a hundred times artificially does not help, because AI values quality and consistency, not quantity. Hiding data inside images or code the model reads poorly does not help either. And arguing with the chatbot in a conversation certainly does not work, since that correction is not saved for other users.
What to watch afterwards
Fixing it once is not enough. AI answers change with every model update and with every new source that appears. It pays to review what assistants say about your brand on a regular basis, note the errors and check whether the corrections take effect.
| Symptom | Likely cause | Action |
|---|---|---|
| Wrong price | Contradictory versions on the site | Unify the price across all pages |
| Invented feature | Mix up with a competitor | Describe your catalogue clearly |
| Outdated fact | Old data in the training set | Publish the current version and date it |
Tools such as Bee LLM let you track these answers daily in Spanish across ChatGPT, Gemini and Perplexity, which helps you notice a new hallucination before it spreads. Even so, the underlying work stays the same: clear, consistent data backed by sources the AI respects.
Measure your AI visibility with Bee LLM
Find out whether ChatGPT, Gemini and Perplexity recommend your brand, benchmark against competitors and get daily tracking. From €19.90/mo, or start free with no card.
Start freeKeep reading: AI search visibility metrics and KPIs · tools comparison.